A two-layer shallow water model for bedload sediment transport: convergence to Saint-Venant-Exner model

A two-layer shallow water type model is proposed to describe bedload sediment transport. The upper layer is filled by water and the lower one by sediment. The key point falls on the definition of the friction laws between the two layers, which are a generalization of those introduced in Fern\'andez-Nieto et al. (ESAIM: M2AN, 51:115-145, 2017). This definition allows to apply properly the two-layer shallow water model for the case of intense and slow bedload sediment transport. Moreover, we prove that the two-layer model converges to a Saint-Venant-Exner system (SVE) including gravitational effects when the ratio between the hydrodynamic and morphodynamic time scales is small. The SVE with gravitational effects is a degenerated nonlinear parabolic system. This means that its numerical approximation is very expensive from a computational point of view, see for example T. Morales de Luna et al. (J. Sci. Comp., 48(1): 258-273, 2011). In this work, gravitational effects are introduced into the two-layer system without such extra computational cost. Finally, we also consider a generalization of the model that includes a non-hydrostatic pressure correction for the fluid layer and the boundary condition at the sediment surface. Numerical tests show that the model provides promising results and behave well in low transport rate regimes as well as in many other situations

Formal deduction of the Saint-Venant-Exner model including arbitrarily sloping sediment beds and associated energy

In this work we present a deduction of the Saint-Venant-Exner model through an asymptotic analysis of the Navier-Stokes equations. A multi-scale analysis is performed in order to take into account that the velocity of the sediment layer is smaller than the one of the fluid layer. This leads us to consider a shallow water type system for the fluid layer and a lubrication Reynolds equation for the sediment one. This deduction provides some improvements with respect to the classical Saint-Venant-Exner model: (i) the deduced model has an associated energy. Moreover, it allows us to explain why classical models do not have an associated energy and how to modify them in order to recover a model with this property. (ii) The model incorporates naturally a necessary modification that must be taken into account in order to be applied to arbitrarily sloping beds. Furthermore, we show that this modification is different of the ones considered classically, and that it coincides with a classical one only if the solution has a constant free surface. (iii) The deduced solid transport discharge naturally depends on the thickness of the moving sediment layer, what allows to ensure sediment mass conservation. Moreover, we include a simplified version of the model for the case of quasi-stationary regimes. Some of these simplified models correspond to the generalization of classical ones such as Meyer-Peter$\&$M\"uller and Ashida-Michiue models. Three numerical tests are presented to study the evolution of a dune for several definition of the repose angle, to see the influence of the proposed definition of the effective shear stress in comparison with the classical one, and by comparing with experimental data.Comment: 44 pages, sumbitted to Advances in Water Resources 17 july 201

Collective decision-making

Collective decision-making is the subfield of collective behaviour concerned with how groups reach decisions. Almost all aspects of behaviour can be considered in a decision-making context, but here we focus primarily on how groups should optimally reach consensus, what criteria decision-makers should optimise, and how individuals and groups should forage to optimise their nutrition. We argue for deep parallels between understanding decisions made by individuals and by groups, such as the decision-guiding principle of value-sensitivity. We also review relevant theory and empirical development for the study of collective decision making, including the use of robots

Collective decision-making

Collective decision-making is the subfield of collective behaviour concerned with how groups reach decisions. Almost all aspects of behaviour can be considered in a decision-making context, but here we focus primarily on how groups should optimally reach consensus, what criteria decision-makers should optimise, and how individuals and groups should forage to optimise their nutrition. We argue for deep parallels between understanding decisions made by individuals and by groups, such as the decision-guiding principle of value-sensitivity. We also review relevant theory and empirical development for the study of collective decision making, including the use of robots

Topological Observables in Semiclassical Field Theories

We give a geometrical set up for the semiclassical approximation to euclidean field theories having families of minima (instantons) parametrized by suitable moduli spaces ${\cal M}$. The standard examples are of course Yang-Mills theory and non-linear $\sigma$-models. The relevant space here is a family of measure spaces \tilde {\cal N} \ra {\cal M}, with standard fibre a distribution space, given by a suitable extension of the normal bundle to ${\cal M}$ in the space of smooth fields. Over $\tilde {\cal N}$ there is a probability measure $d\mu$ given by the twisted product of the (normalized) volume element on ${\cal M}$ and the family of gaussian measures with covariance given by the tree propagator $C_\phi$ in the background of an instanton $\phi \in {\cal M}$. The space of ``observables", i.e. measurable functions on ($\tilde {\cal N}, \, d\mu$), is studied and it is shown to contain a topological sector, corresponding to the intersection theory on ${\cal M}$. The expectation value of these topological ``observables" does not depend on the covariance; it is therefore exact at all orders in perturbation theory and can moreover be computed in the topological regime by setting the covariance to zero.Comment: 11 page

COVID-19: Open-data resources for monitoring, modeling, and forecasting the epidemic

We provide an insight into the open-data resources pertinent to the study of the spread of the Covid-19 pandemic and its control. We identify the variables required to analyze fundamental aspects like seasonal behavior, regional mortality rates, and effectiveness of government measures. Open-data resources, along with data-driven methodologies, provide many opportunities to improve the response of the different administrations to the virus. We describe the present limitations and difficulties encountered in most of the open-data resources. To facilitate the access to the main open-data portals and resources, we identify the most relevant institutions, on a global scale, providing Covid-19 information and/or auxiliary variables (demographics, mobility, etc.). We also describe several open resources to access Covid-19 datasets at a country-wide level (i.e., China, Italy, Spain, France, Germany, US, etc.). To facilitate the rapid response to the study of the seasonal behavior of Covid-19, we enumerate the main open resources in terms of weather and climate variables. We also assess the reusability of some representative open-data sources

Anterior Segment Optical Coherence Tomography Imaging of Filtering Blebs after Deep Sclerectomy with Esnoper-Clip Implant: One-year Follow-up

Purpose: To describe the technique of deep sclerectomy with the new Esnoper-Clip® implant, the clinical outcome and the anatomic characteristics of filtering blebs, using anterior segment optical coherence tomography (AS-OCT). Methods: A prospective case-series study was conducted in five eyes (5 patients) with open angle glaucoma. The fornixbased deep sclerectomy with Esnoper-Clip® implant was done by the same surgeon. In one case, mitomycin C was used during surgery. All participants underwent a complete ophthalmic examination and AS-OCT (Visante®) preoperatively, then at each follow-up visit, at 1 day, 1 week, 1 month, 6 months and 1 year postoperatively. Scans were obtained through sagittal and transversal plans to the implant. Results: Intraocular pressure (IOP) was significantly reduced (p < 0.05) from a mean preoperative value of 23.4 ± 8.6 mm Hg (n = 3.8 glaucoma medications) to a postoperative value of 6.0 ± 2.5 (n = 0), 10.6 ± 5.4 (n = 0), 13 ± 1.6 (n = 0.4), 12.4 ± 2.1 (n = 0.2) and 14.4 ± 1.5 (n = 0.2) at 1 day, 1 week, 1 month, 6 months and 1 year respectively. AS-OCT allowed the visualization of the two plates of the implant (scleral and suprasciliary), the trabeculodescemetic membrane and the hyporeflective spaces in the bleb wall thickness and in suprascleral and suprachoroidal localizations. An immediate postoperative hypotony and an anteriorization of the implant associated to trabeculodescemetic membrane rupture, were detected, although without significant clinical repercussions. Conclusion: Our first five deep sclerectomy with Esnoper-Clip implantation analysis suggest an effective and well-tolerated method to reduce IOP. AS-OCT is a noninvasive imaging technique that allows the anatomic analysis of the drainage mechanisms after glaucoma surgery.info:eu-repo/semantics/publishedVersio

Model of the best-of-N nest-site selection process in honeybees

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony’s fitness. To date, the nest-site selection process has mostly been modelled and theoretically analysed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision process dynamics qualitatively change. In this work, we extend previous analyses of a valuesensitive decision-making mechanism to a decision process among N nests. First, we present the decisionmaking dynamics in the symmetric case of N equal-quality nests. Then, we generalise our findings to a best-of-N decision scenario with one superior nest and N – 1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signalling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signalling behaviours. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signalling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signalling ratio